Search Results (45)

This article focuses on the fire safety risks associated with conventional glass–aluminum façades—with a particular focus on stick and unitized curtain walling systems—providing an overview of possible fire spread mechanisms, considering the role of the curtain wall in maintaining compartmentation at the spandrel zone. First, it analyzes some of the relevant requirements of different European building regulations. Then, it provides a test evidence-based critical analysis of the gaps and loopholes in the relevant fire resistance standard for partial curtain wall configurations (EN 1364-4), where the evaluation of the propagation within the façade system is not necessarily considered in the fire-resistant spandrel zone. Finally, it presents a proposal for addressing these gaps in the form of a theoretical concept for a new test configuration and additional assessment criteria. This is followed by an initial experimental analysis of the concept. The standard testing campaign showed that temperature rise in mullions can exceed 180 °C after 30 min if limiting measures are not considered in the façade design. However, this can be only detected if framing is in the non-exposed area of the sample, being part of the evaluation surface. Meanwhile, differences are detected between the results from standard and new assessment criteria in the new configuration proposed, including a more rapid temperature rise for framing elements (207 K in a second level mullion at minute 90) than for the common non-exposed assessment surface of the sample (172 K at the same time) in cases where cavities are not protected. Accordingly, the proposed configuration successfully detected vertical temperature transfer within mullions, which can remain undetected in standard EN 1364-4 tests, highlighting the potential for fire spread even in EI120-rated assemblies. Full article

This study presents a simulation-based damage modeling and fatigue risk assessment of a reusable ceramic matrix composite thruster designed for short-duration, green bipropellant propulsion systems. The thruster is constructed from a fiber-reinforced ultra-high temperature ceramic matrix composite composed of zirconium diboride, silicon carbide, and carbon fibers. Time-resolved thermal and structural simulations are conducted on a validated thruster geometry to characterize the severity of early-stage thermal shock, stress buildup, and potential degradation pathways. Unlike traditional fatigue studies that rely on empirical fatigue constants or Paris-law-based crack-growth models, this work introduces a simulation-derived stress-margin envelope methodology that incorporates ±20% variability in temperature-dependent material strength, offering a physically grounded yet conservative risk estimate. From this, a normalized risk index is derived to evaluate the likelihood of damage initiation in critical regions over the 0–10 s firing window. The results indicate that the convergent throat region experiences a peak thermal gradient rate of approximately 380 K/s, with the normalized thermal shock index exceeding 43. Stress margins in this region collapse by 2.3 s, while margin loss in the flange curvature appears near 8 s. These findings are mapped into green, yellow, and red risk bands to classify operational safety zones. All the results assume no active cooling, representing conservative operating limits. If regenerative or ablative cooling is implemented, these margins would improve significantly. The framework established here enables a transparent, reproducible methodology for evaluating lifetime safety in ceramic propulsion nozzles and serves as a foundational tool for fatigue-resilient component design in green space engines. Full article

Forest fires in the Hindu Kush Himalaya (HKH) region are increasing in frequency and severity, driven by climate variability, prolonged dry periods, and human activity. Nepal, a critical part of the HKH, recorded over 22,700 forest fire events in the past decade, with fire incidence nearly doubling in 2023. Despite this growing threat, operational early warning systems remain limited. This study presents Nepal’s first high-resolution early fire risk outlook system, developed by adopting the Canadian Fire Weather Index (FWI) using meteorological forecasts from the High-Impact Weather Assessment Toolkit (HIWAT). The system generates daily and two-day forecasts using a fully automated Python-based workflow and publishes results as Web Map Services (WMS). Model validation against MODIS, VIIRS, and ground fire records for 2023 showed that over 80% of fires occurred in zones classified as Moderate to Very High risk. Spatiotemporal analysis confirmed fire seasonality, with peaks in mid-April and over 65% of fires occurring in forested areas. The system’s integration of satellite data and high-resolution forecasts improves the spatial and temporal accuracy of fire danger predictions. This research presents a novel, scalable, and operational framework tailored for data-scarce and topographically complex regions. Its transferability holds substantial potential for strengthening anticipatory fire management and climate adaptation strategies across the HKH and beyond. Full article

Conveyor belts are critical in various industries, particularly in the barrier eddy current separator systems used in recycling processes. However, hidden issues, such as belt misalignment, excessive heat that can lead to fire hazards, and the presence of sharp or irregularly shaped materials, reduce operational efficiency and pose serious threats to the health and safety of personnel on the production floor. This study presents an intelligent monitoring and protection system for barrier eddy current separator conveyor belts designed to safeguard machinery and human workers simultaneously. In this system, a thermal camera continuously monitors the surface temperature of the conveyor belt, especially in the area above the magnetic drum—where unwanted ferromagnetic materials can lead to abnormal heating and potential fire risks. The system detects temperature anomalies in this critical zone. The early detection of these risks triggers audio–visual alerts and IoT-based warning messages that are sent to technicians, which is vital in preventing fire-related injuries and minimizing emergency response time. Simultaneously, a machine vision module autonomously detects and corrects belt misalignment, eliminating the need for manual intervention and reducing the risk of worker exposure to moving mechanical parts. Additionally, a line-scan camera integrated with the YOLOv11 AI model analyses the shape of materials on the conveyor belt, distinguishing between rounded and sharp-edged objects. This system enhances the accuracy of material separation and reduces the likelihood of injuries caused by the impact or ejection of sharp fragments during maintenance or handling. The YOLOv11n-seg model implemented in this system achieved a segmentation mask precision of 84.8 percent and a recall of 84.5 percent in industry evaluations. Based on this high segmentation accuracy and consistent detection of sharp particles, the system is expected to substantially reduce the frequency of sharp object collisions with the BECS conveyor belt, thereby minimizing mechanical wear and potential safety hazards. By integrating these intelligent capabilities into a compact, cost-effective solution suitable for real-world recycling environments, the proposed system contributes significantly to improving workplace safety and equipment longevity. This project demonstrates how digital transformation and artificial intelligence can play a pivotal role in advancing occupational health and safety in modern industrial production. Full article

In recent years, the frequency and severity of large-scale forest fires have increased globally, threatening forest ecosystems, human lives, and property while potentially triggering cascading ecological and social crises. Despite significant advancements in remote sensing-based forest fire monitoring, early warning systems, and fire risk zoning, post-fire thermal damage assessment remains insufficiently addressed. This study introduces an innovative approach combining multispectral imaging with a dual annealing constrained optimization algorithm to enable dynamic monitoring of fire temperature distribution. Based on this method, we develop a dynamic thermal damage assessment model to quantify thermal impacts during forest fires. The proposed model provides valuable insights for defining thermal damage zones, optimizing evacuation strategies, and supporting firefighting operations, ultimately enhancing emergency response and forest fire management efficiency. Full article

Safety zones protect firefighters from bodily injury and death caused by exposure to dangerous heat levels. These zones are defined by maintaining a safe distance from combustible fuels, a safe separation distance (SSD) derived from flame height. This study aimed to determine safety zones, integrating an existing automated identification-of-safety-zone model with vegetation height derived from a freely available high-resolution global canopy height dataset for Manavgat Forest Management Directorate (FMD) in Türkiye. Flame height, terrain slope, size of a safety zone, and distance to the closest road were also used as input in this model. The results indicated that vegetation height from high-resolution global canopy height offered promising results for determining potential safety zones (SZs) associated with SSD. Integrating the global canopy height dataset into the existing model could assist in determining the safety zone in the absence of lidar. Thus, this spatial model would provide a framework for decision-makers to develop fire prevention and suppression strategies for higher fire risk areas, especially before and during a fire. Full article

Mountain photovoltaic (PV) power stations cover vast areas and contain dense equipment. Once direct current arc faults occur in PV modules, they can pose a serious thermal threat to surrounding facilities and combustible materials, potentially resulting in a PV array fire accident. In this work, a series of PV module fire experiments were conducted to investigate the burning characteristics of PV modules exposed to the pool fire. The burning process, burning damage extent, and temperature distribution were measured and analyzed. The results showed that the surfaces of PV modules exhibited different burning characteristics due to the pool fire. Based on different characteristics, the front side was classified into four zones: intact zone, delamination zone, carbonization zone and burn-through zone. The back side was similarly divided into four zones: undamaged backsheet zone, burnt TPT zone, cell detachment zone and burn-through zone. Meanwhile, the burning process and surface temperature rise rate of intact PV modules were significantly lower than those of cracked modules at the same inclination angle. Cracked modules exhibited a heightened susceptibility to being rapidly burnt through by the pool fire. As the inclination angle increased from 0° to 60°, the burning damage extent and the expansion rate of high-temperature regions initially ascended and subsequently decreased, reaching their maximum at the inclination angle of 15°. These findings can offer valuable insights that can serve as a reference for the fire protection design and risk assessment of mountain PV power stations, ensuring their safe operation. Full article

Rural fires are becoming increasingly impactful, not only due to their rapid and intense spread but also because of the growing number of people affected. In Portugal, numerous remote housing clusters are difficult to access and are primarily occupied by seniors or individuals with disabilities. These areas are situated in high-risk wildfire zones. Therefore, it is crucial to document the locations of the individuals who are most at risk to ensure that relief efforts can be focused on and directed towards them in case of emergency. The aim of this paper is to propose an inventory plan for communities at risk of wildfire, requiring the involvement of parish councils. The plan involves the use of simple and cost-free georeferencing tools (such as Mymaps of Google) to enable these organizations to assist in municipal emergency planning and facilitate the exchange of real-time information. The outcomes of this paper will be demonstrated in three parishes in mainland Portugal, where the key benefits and limitations were identified. The goal is to enhance the project for potential replication in other areas. Full article

Forest fire risk mapping is an essential measure for forest fire management. Quickly and precisely assessing forest fire risks, rationally planning fire risk zones, and scientifically allocating firefighting resources are of great significance for mitigating the increasingly severe threat of forest fires. This study utilized the random forest (RF) algorithm and the Fuzzy Analytic Network Process (FANP) to conduct a forest fire risk-zoning study in the protection and development belt of Wuyishan National Park. The findings revealed that some areas in the western and southern parts of this region have relatively high fire risk levels. Particularly, forest fire prevention and control in the western area need to be strengthened to prevent potential hazards to Wuyishan National Park. The accuracy of the FANP model was as high as 88.5%; areas with fire risk levels of grade 3 and above could control 98.44% of forest fires, and the proportion of areas with fire risk levels of grade 4 and above was 33.41%, which could control 65.63% of forest fires. This finding indicates that the FANP has preferable applicability in small-scale forest fire risk zoning and can offer more reliable decision-making support and reference basis for regional forest fire management. Full article

Wildfire ignitions are often linked to environmental and climatic factors, but human behavior plays a critical role, particularly in rural southern Europe. However, tools to quantify the probability of human-caused ignitions are lacking. This study addresses this by developing a human behavior wildfire ignition probability index focused on mainland Portugal, a region historically vulnerable to wildfires. Statistical analyses, including multicollinearity checks and a Generalized Linear Model, were used to analyze ignition data, while geospatial analyses estimated the ignition probabilities for 2021 and 2022. Inputs included human activity indicators, land use types, and proximity to residential roads. The resulting probability maps identified high-risk areas, particularly in forested zones and near residential roads. These maps closely aligned with documented human-caused ignitions, confirming the model’s reliability. The index is a robust tool for identifying high-risk areas and has significant potential to improve fire prevention strategies by targeting the most vulnerable regions. Future research should explore its integration into forecasting systems for real-time fire prevention and response strategies as well as its adaptation to other regions with similar wildfire risks. Full article

The paper discusses potential hazards at hydrogen refueling stations for transportation vehicles: cars and trucks. The main hazard analyzed here is an uncontrolled gas release due to a failure in one of the structures in the station: storage tanks of different pressure levels or a dispenser. This may lead to a hydrogen cloud occurring near the source of the release or at a given distance. The range of the cloud was analyzed in connection to the amount of the released gas and the wind velocity. The results of the calculations were compared for chosen structures in the station. Then potential fires and explosions were investigated. The hazard zones were calculated with respect to heat fluxes generated in the fires and the overpressure generated in explosions. The maximum ranges of these zones vary from about 14 to 30 m and from about 9 to 14 m for a fires and an explosions of hydrogen, respectively. Finally, human death probabilities are presented as functions of the distance from the sources of the uncontrolled hydrogen releases. These are shown for different amounts and pressures of the released gas. In addition, the risk of human death is determined along with the area, where it reaches the highest value in the whole station. The risk of human death in this area is 1.63 × 10⁻⁵ [1/year]. The area is approximately 8 square meters. Full article

Disassembly is a key step in remanufacturing, especially for end-of-life (EoL) products such as electric vehicle (EV) batteries, which are challenging to dismantle due to uncertainties in their condition and potential risks of fire, fumes, explosions, and electrical shock. To address these challenges, this paper presents a robotic teleoperation system that leverages augmented reality (AR) and digital twin (DT) technologies to enable a human operator to work away from the danger zone. By integrating AR and DTs, the system not only provides a real-time visual representation of the robot’s status but also enables remote control via gesture recognition. A bidirectional communication framework established within the system synchronises the virtual robot with its physical counterpart in an AR environment, which enhances the operator’s understanding of both the robot and task statuses. In the event of anomalies, the operator can interact with the virtual robot through intuitive gestures based on information displayed on the AR interface, thereby improving decision-making efficiency and operational safety. The application of this system is demonstrated through a case study involving the disassembly of a busbar from an EoL EV battery. Furthermore, the performance of the system in terms of task completion time and operator workload was evaluated and compared with that of AR-based control methods without informational cues and ‘smartpad’ controls. The findings indicate that the proposed system reduces operation time and enhances user experience, delivering its broad application potential in complex industrial settings. Full article

This study evaluates bushfire smoke as a workplace hazard for firefighters by characterising its chemical composition and potential health risks in Western Australia. Portable Fourier Transform Infrared (FTIR) spectrometry was used to measure airborne chemical concentrations at prescribed burns across five regions, including peat (acid sulphate) fire events. Samples were collected during both flaming and smouldering phases, as well as in perceived “clear” air resting zones. Results indicated that carbon monoxide (CO) was the dominant gas, reaching concentrations of 205 ppm at the fire front, followed by nitrogen monoxide (26 ppm) and methane (19 ppm). Peat fires produced distinct profiles, with ammonia (21.5 ppm) and sulphur dioxide (9.5 ppm) concentrations higher than those observed in typical bushfires. Smouldering phases emitted higher chemical concentrations than flaming phases 75% of the time. Even clear air zones contained measurable chemicals, with CO levels averaging 18 ppm, suggesting that firefighters are not free from exposure during rest periods. These findings highlight the need for fit-for-purpose respiratory protective equipment (RPE) and improved rest protocols to minimise exposure. The study underscores the importance of comprehensive health monitoring programs for firefighters to mitigate long-term health risks. Full article

The release of mercury (Hg) from coal-fired power plants (CPPs) into local ecosystems poses substantial environmental and health hazards. This study was conducted in Chungcheong-nam-do, South Korea, a region featuring over half of the country’s coal power facilities, to estimate the impacts of CPPs on Hg distribution in forest ecosystems. By analyzing Hg concentrations in pine tree rings and soil at 21 locations around CPPs and comparing them to control sites and industrial zones, we present a nuanced understanding of the effects of CPPs on Hg concentration. The analysis of Hg concentrations in tree rings showed a significant decrease in Hg levels as the distance from the power plants increased, suggesting that CPPs primarily influence Hg distribution in trees within a 25 km radius. In contrast, soil Hg concentrations did not exhibit a clear trend. This may reflect the limitations of this study in accounting for the physicochemical properties of the soil at each sampling site. Nevertheless, the Potential Ecological Risk Index for soil Hg contamination indicated a higher risk rating within a 1 km radius of the CPPs compared to other locations. Hg concentrations in tree rings have shown a steady decline since the 1970s, suggesting the positive effects of air pollution regulations. This also highlights the value of tree core samples as effective tools for monitoring historical Hg pollution. Furthermore, the higher historical concentrations of Hg in tree rings imply that trees may have acted as sinks for atmospheric Hg in the past. Full article

Wildfires have long been one of the critical environmental disasters that require a careful monitoring system. An intelligent system has the potential to both prevent/extinguish the fire and deliver urgent requirements postfire. In recent years, unmanned aerial vehicles (UAVs), with the ability to detect missions in high-risk areas, have been gaining increasing interest, particularly in forest fire monitoring. Taking a large-scale area involved in a fire into consideration, a single UAV is often insufficient to accomplish the task of covering the whole disaster zone. This poses the challenge of multi-UAVs optimum path planning with a key focus on limitations such as energy constraints and connectivity. To narrow down this issue, this paper proposes a deep reinforcement learning-based trajectory planning approach for multi-UAVs that permits UAVs to extract the required information within the disaster area on time. A target area is partitioned into several identical subareas in terms of size to enable UAVs to perform their patrol duties over the subareas. This subarea-based arrangement converts the issue of trajectory planning into allowing UAVs to frequently visit each subarea. Each subarea is initiated with a risk level by creating a fire risk map optimizing the UAV patrol route more precisely. Through a set of simulations conducted with a real trace of the dataset, the performance outcomes confirmed the superiority of the proposed idea. Full article